Code
import os
#os.system('pip install sweetviz')
import os
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import explained_variance_score
from sklearn.metrics import confusion_matrix
from sklearn.model_selection import train_test_splithttps://www.kaggle.com/competitions/house-prices-advanced-regression-techniques
| Id | MSSubClass | MSZoning | LotFrontage | LotArea | Street | Alley | LotShape | LandContour | Utilities | ... | PoolArea | PoolQC | Fence | MiscFeature | MiscVal | MoSold | YrSold | SaleType | SaleCondition | SalePrice | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 60 | RL | 65.0 | 8450 | Pave | NaN | Reg | Lvl | AllPub | ... | 0 | NaN | NaN | NaN | 0 | 2 | 2008 | WD | Normal | 208500 |
| 1 | 2 | 20 | RL | 80.0 | 9600 | Pave | NaN | Reg | Lvl | AllPub | ... | 0 | NaN | NaN | NaN | 0 | 5 | 2007 | WD | Normal | 181500 |
| 2 | 3 | 60 | RL | 68.0 | 11250 | Pave | NaN | IR1 | Lvl | AllPub | ... | 0 | NaN | NaN | NaN | 0 | 9 | 2008 | WD | Normal | 223500 |
| 3 | 4 | 70 | RL | 60.0 | 9550 | Pave | NaN | IR1 | Lvl | AllPub | ... | 0 | NaN | NaN | NaN | 0 | 2 | 2006 | WD | Abnorml | 140000 |
| 4 | 5 | 60 | RL | 84.0 | 14260 | Pave | NaN | IR1 | Lvl | AllPub | ... | 0 | NaN | NaN | NaN | 0 | 12 | 2008 | WD | Normal | 250000 |
5 rows × 81 columns
| Id | MSSubClass | LotFrontage | LotArea | OverallQual | OverallCond | YearBuilt | YearRemodAdd | MasVnrArea | BsmtFinSF1 | ... | WoodDeckSF | OpenPorchSF | EnclosedPorch | 3SsnPorch | ScreenPorch | PoolArea | MiscVal | MoSold | YrSold | SalePrice | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| count | 1460.000000 | 1460.000000 | 1201.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1452.000000 | 1460.000000 | ... | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 | 1460.000000 |
| mean | 730.500000 | 56.897260 | 70.049958 | 10516.828082 | 6.099315 | 5.575342 | 1971.267808 | 1984.865753 | 103.685262 | 443.639726 | ... | 94.244521 | 46.660274 | 21.954110 | 3.409589 | 15.060959 | 2.758904 | 43.489041 | 6.321918 | 2007.815753 | 180921.195890 |
| std | 421.610009 | 42.300571 | 24.284752 | 9981.264932 | 1.382997 | 1.112799 | 30.202904 | 20.645407 | 181.066207 | 456.098091 | ... | 125.338794 | 66.256028 | 61.119149 | 29.317331 | 55.757415 | 40.177307 | 496.123024 | 2.703626 | 1.328095 | 79442.502883 |
| min | 1.000000 | 20.000000 | 21.000000 | 1300.000000 | 1.000000 | 1.000000 | 1872.000000 | 1950.000000 | 0.000000 | 0.000000 | ... | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 2006.000000 | 34900.000000 |
| 25% | 365.750000 | 20.000000 | 59.000000 | 7553.500000 | 5.000000 | 5.000000 | 1954.000000 | 1967.000000 | 0.000000 | 0.000000 | ... | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 5.000000 | 2007.000000 | 129975.000000 |
| 50% | 730.500000 | 50.000000 | 69.000000 | 9478.500000 | 6.000000 | 5.000000 | 1973.000000 | 1994.000000 | 0.000000 | 383.500000 | ... | 0.000000 | 25.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 6.000000 | 2008.000000 | 163000.000000 |
| 75% | 1095.250000 | 70.000000 | 80.000000 | 11601.500000 | 7.000000 | 6.000000 | 2000.000000 | 2004.000000 | 166.000000 | 712.250000 | ... | 168.000000 | 68.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 8.000000 | 2009.000000 | 214000.000000 |
| max | 1460.000000 | 190.000000 | 313.000000 | 215245.000000 | 10.000000 | 9.000000 | 2010.000000 | 2010.000000 | 1600.000000 | 5644.000000 | ... | 857.000000 | 547.000000 | 552.000000 | 508.000000 | 480.000000 | 738.000000 | 15500.000000 | 12.000000 | 2010.000000 | 755000.000000 |
8 rows × 38 columns
| MSZoning | Street | Alley | LotShape | LandContour | Utilities | LotConfig | LandSlope | Neighborhood | Condition1 | ... | GarageFinish | GarageQual | GarageCond | PavedDrive | PoolQC | Fence | MiscFeature | SaleType | SaleCondition | role | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| count | 1460 | 1460 | 91 | 1460 | 1460 | 1460 | 1460 | 1460 | 1460 | 1460 | ... | 1379 | 1379 | 1379 | 1460 | 7 | 281 | 54 | 1460 | 1460 | 1460 |
| unique | 5 | 2 | 2 | 4 | 4 | 2 | 5 | 3 | 25 | 9 | ... | 3 | 5 | 5 | 3 | 3 | 4 | 4 | 9 | 6 | 1 |
| top | RL | Pave | Grvl | Reg | Lvl | AllPub | Inside | Gtl | NAmes | Norm | ... | Unf | TA | TA | Y | Gd | MnPrv | Shed | WD | Normal | train |
| freq | 1151 | 1454 | 50 | 925 | 1311 | 1459 | 1052 | 1382 | 225 | 1260 | ... | 605 | 1311 | 1326 | 1340 | 3 | 157 | 49 | 1267 | 1198 | 1460 |
4 rows × 44 columns
Missing Data
Id 0
MSSubClass 0
MSZoning 0
LotFrontage 259
LotArea 0
...
YrSold 0
SaleType 0
SaleCondition 0
SalePrice 0
role 0
Length: 82, dtype: int64